Protein analysis by mass spectrometry is largely done via a bottom-up, data-dependent method. With this approach, proteins are first digested by enzymes into peptides. These peptides are then separated either by one or more dimensions of liquid chromatography. Following separation, the eluting peptides are ionized and analyzed with the mass spectrometer using an MS1 “survey scan”. From this initial mass spectral analysis, precursors are selected for subsequent analysis using a set of criteria (e.g., precursor charge state). These selected precursors are further interrogated by MS/MS analysis (e.g., via isolation, fragmentation, and m/z analysis).
This approach is quite effective at covering a very wide range of peptides in a very short amount of time. However, due to the limited dynamic range of the MS1 analysis, and the stochastic nature of data-dependent precursor sampling, the depth and reproducibility of this approach is often poor. For example, it is rare that this approach provides complete coverage of biological functional groups or pathways (e.g., it is unlikely a data-dependent analysis would cover all the human kinases). These workflow limitations often result in poor overlap between replicate experiments.
Targeted proteomics approaches, such as selected reaction monitoring (SRM), multiple reaction monitoring (MRM), and parallel reaction monitoring (PRM), are the traditional alternatives to the data-dependent approach. In lieu of selecting precursors from an MS1 survey spectrum, the instrument dwells upon select m/z regions that are informed by a list that is populated by the user before the analysis. That is, the instrument continuously collects MS/MS spectra, independent of whether there is any detectable signal in an MS1 spectrum. By specifically dwelling on prespecified precursors, these methods are capable of much higher sensitivity and reproducibility than the data-dependent workflow.
However, one of the main compromises with these targeted analyses is breadth. Dwelling upon low abundance precursors comes at the cost of interrogating higher abundance species. Also, without any pre-screening of the eluting peptides (i.e., MS1 survey spectra), it is expected that some portion of the targeted MS/MS analyses will occur when there is no precursor present (i.e., MS/MS spectra will be collected while the precursor isn't eluting). These concerns can be somewhat mitigated by employing complex retention time scheduling—that is, along with the list of precursor targets the user provides a list of retention times. However, scheduling targeted scans in this manner requires precise knowledge of peptide retention times. These times are specific to the chromatographic setup, and the utility of these times are heavily contingent upon the reproducibility of the chromatographic separation.
As an alternative to these traditional approaches, two labs have published workflows that attempt to realize the depth and reproducibility of the targeted workflow while still leveraging the ease of use of the data-dependent approach (see Gallien et al., “Large-Scale Targeted Proteomics Using Internal Standard Triggered-Parallel Reaction Monitoring (IS-PRM)”, Mol. Cell. Proteomics, Vol. 14, No. 6, pp. 1630-44 (2015); Yan et al., “Index-ion Triggered MS2 Ion Quantification: A Novel Proteomics Approach for Reproducible Detection and Quantification of Targeted Proteins in Complex Mixtures”, Mol. Cell. Proteomics, Vol. 10, No. 3, M110.005611 (2011)). These workflows begin with the addition of heavy peptide standards to the analytical sample. These heavy standards have sequences that are analogous to endogenous peptides of interest. By incorporating specific heavy isotopes, these standards differ in mass from the endogenous form of the peptide; however, their retention times match exactly. In the published workflows, the mass spectrometer method includes low-quality targeted scans on the spiked-in standards. Following acquisition of the targeted MS/MS transitions/spectra, the data is analyzed, and if certain conditions are met the instrument triggers a high-quality MS/MS analysis on the expected location of the endogenous form of the peptide.
While these workflows have been partially successful at addressing the limitations and disadvantages of the established data-dependent and targeted methods, they tend to have a steep tradeoff between sensitivity and selectivity, with one of the published workflows offering good sensitivity but limited selectivity, and the other exhibiting excellent selectivity with modest sensitivity. Furthermore, both workflows rely on retention time scheduling to achieve acceptable duty cycle and selectivity, which increases method setup complexity, places stress on sample availability, and can compromise robustness, particularly where run-to-run variation of chromatographic separation exits.